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# glm-edge-4b-chat_a13793987324669952305886 ---
frameworks:
- Pytorch
license: other
tasks:
- text-generation
glm-edge-4b-chat domain:
- nlp
language:
- cn
- en
tools:
- vllm、fastchat、llamacpp、AdaSeq
---
# GLM-Edge-1.5B-Chat
Read this in [English](README_en.md)
## 使用 transformers 库进行推理
### 安装
请安装源代码的transformers库。
```shell
pip install git+https://github.com/huggingface/transformers.git
```
### 推理
```python
from modelscope import AutoModelForCausalLM, AutoTokenizer
MODEL_PATH = "ZhipuAI/glm-edge-4b-chat"
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")
message = [{"role": "user", "content": "hello!"}]
inputs = tokenizer.apply_chat_template(
message,
return_tensors="pt",
add_generation_prompt=True,
return_dict=True,
).to(model.device)
generate_kwargs = {
"input_ids": inputs["input_ids"],
"attention_mask": inputs["attention_mask"],
"max_new_tokens": 128,
"do_sample": False,
}
out = model.generate(**generate_kwargs)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
```
## 协议
本模型的权重的使用则需要遵循 [LICENSE](LICENSE)。

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# GLM-Edge-1.5B-Chat
中文阅读, 点击[这里](README_zh.md)
## Inference with Transformers
### Installation
Install the transformers library from the source code:
```shell
pip install git+https://github.com/huggingface/transformers.git
```
### Inference
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
MODEL_PATH = "THUDM/glm-edge-4b-chat"
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")
message = [{"role": "user", "content": "hello!"}]
inputs = tokenizer.apply_chat_template(
message,
return_tensors="pt",
add_generation_prompt=True,
return_dict=True,
).to(model.device)
generate_kwargs = {
"input_ids": inputs["input_ids"],
"attention_mask": inputs["attention_mask"],
"max_new_tokens": 128,
"do_sample": False,
}
out = model.generate(**generate_kwargs)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))
```
## License
The usage of this model’s weights is subject to the terms outlined in the [LICENSE](LICENSE).

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{
"architectures": [
"GlmForCausalLM"
],
"partial_rotary_factor": 1.0,
"attention_bias": false,
"attention_dropout": 0.0,
"eos_token_id": [
59246,
59253,
59255
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"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 3072,
"initializer_range": 0.02,
"intermediate_size": 8192,
"max_position_embeddings": 8192,
"model_type": "glm",
"num_attention_heads": 24,
"num_hidden_layers": 40,
"num_key_value_heads": 6,
"pad_token_id": 59246,
"rms_norm_eps": 1e-05,
"rope_theta": 10000.0,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.47.0.dev0",
"use_cache": true,
"vocab_size": 59264
}

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{
"_from_model_config": true,
"eos_token_id": [
59246,
59253,
59255
],
"pad_token_id": 59246,
"transformers_version": "4.47.0.dev0"
}

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483534
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145
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"[sMASK]",
"<sop>",
"<eop>",
"<|system|>",
"<|user|>",
"<|assistant|>",
"<|observation|>",
"<|begin_of_image|>",
"<|end_of_image|>",
"<|begin_of_video|>",
"<|end_of_video|>"
],
"chat_template": "{% for item in messages %}{% if item['role'] == 'system' %}<|system|>\n{{ item['content'] }}{% elif item['role'] == 'user' %}<|user|>\n{{ item['content'] }}{% elif item['role'] == 'assistant' %}<|assistant|>\n{{ item['content'] }}{% endif %}{% endfor %}{% if add_generation_prompt %}<|assistant|>\n{% endif %}",
"clean_up_tokenization_spaces": false,
"do_lower_case": false,
"eos_token": "<|endoftext|>",
"model_input_names": [
"input_ids",
"attention_mask"
],
"model_max_length": 8192,
"pad_token": "<|endoftext|>",
"padding_side": "left",
"remove_space": false,
"tokenizer_class": "PreTrainedTokenizerFast"
}